Journal of System Simulation
Abstract
Abstract: Aiming at the problem that the traditional lithium battery model has poor adaptive ability in SOC estimation and the local estimation accuracy of the single SOC estimation algorithm is low, online identification of model parameters with Multi-Innovation Stochastic Gradient algorithm and method of weighted online estimation of SOC was proposed. The results of lithium-ion battery model parameters online identification updated in real time, realizing lithium-ion battery model adaptive. Aiming at the estimation of SOC, a method of weighted online estimation method based on the PI (proportion and integral) regulator's OCV combined with Ah (an integral method) was proposed. Weights updated in real time according to SOC-E0 piecewise linear curve slope. The proposed method solved that the estimation error of SOC with OCV is large and Ah method is difficult to determine the initial value and cumulative error. Besides, the proposed method also solved the problem of online estimation of above two method. The feasibility of the method is demonstrated from the theoretical analysis, and the results of MATLAB simulation show that the proposed method has high estimation accuracy.
Recommended Citation
Sun, Haohao; Pan, Tinglong; and Wu, Dinghui
(2020)
"Weighted Online Estimation of SOC Based on Adaptive Battery Model,"
Journal of System Simulation: Vol. 29:
Iss.
8, Article 6.
DOI: 10.16182/j.issn1004731x.joss.201708006
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol29/iss8/6
First Page
1677
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.201708006
Last Page
1684
CLC
TP391.9
Recommended Citation
Sun Haohao, Pan Tinglong, Wu Dinghui. Weighted Online Estimation of SOC Based on Adaptive Battery Model[J]. Journal of System Simulation, 2017, 29(8): 1677-1684.
DOI
10.16182/j.issn1004731x.joss.201708006
Included in
Artificial Intelligence and Robotics Commons, Computer Engineering Commons, Numerical Analysis and Scientific Computing Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Systems Science Commons